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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- tweet_eval |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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base_model: google/electra-small-discriminator |
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model-index: |
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- name: electra-5-epoch-sentiment |
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results: |
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- task: |
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type: text-classification |
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name: Text Classification |
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dataset: |
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name: tweet_eval |
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type: tweet_eval |
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config: sentiment |
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split: test |
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args: sentiment |
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metrics: |
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- type: accuracy |
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value: 0.6893520026050146 |
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name: Accuracy |
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- type: precision |
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value: 0.6913776305729754 |
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name: Precision |
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- type: recall |
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value: 0.6893520026050146 |
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name: Recall |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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TOKENIZER & TRAINER CORRUPTED |
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# electra-5-epoch-sentiment |
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This model is a fine-tuned version of [google/electra-small-discriminator](https://huggingface.co/google/electra-small-discriminator) on the tweet_eval dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7949 |
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- Accuracy: 0.6894 |
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- Precision: 0.6914 |
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- Recall: 0.6894 |
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- Micro-avg-recall: 0.6894 |
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- Micro-avg-precision: 0.6894 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | Micro-avg-recall | Micro-avg-precision | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:----------------:|:-------------------:| |
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| 0.5949 | 1.0 | 2851 | 0.6963 | 0.6926 | 0.6943 | 0.6926 | 0.6926 | 0.6926 | |
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| 0.6502 | 2.0 | 5702 | 0.7348 | 0.6911 | 0.6929 | 0.6911 | 0.6911 | 0.6911 | |
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| 0.556 | 3.0 | 8553 | 0.7322 | 0.6943 | 0.6952 | 0.6943 | 0.6943 | 0.6943 | |
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| 0.4561 | 4.0 | 11404 | 0.7601 | 0.6895 | 0.6916 | 0.6895 | 0.6895 | 0.6895 | |
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| 0.471 | 5.0 | 14255 | 0.7949 | 0.6894 | 0.6914 | 0.6894 | 0.6894 | 0.6894 | |
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### Framework versions |
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- Transformers 4.33.0 |
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- Pytorch 2.0.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.13.3 |
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